This Case Shows Specific Expertise. Find the Companies with the Skills Your Project Demands!

You're viewing one of tens of thousands of real cases compiled on Many.dev. Each case demonstrates specific, tangible expertise.

But how do you find the company that possesses the exact skills and experience needed for your project? Forget generic filters!

Our unique AI system allows you to describe your project in your own words and instantly get a list of companies that have already successfully applied that precise expertise in similar projects.

Create a free account to unlock powerful AI-powered search and connect with companies whose expertise directly matches your project's requirements.

Automated Price and Stock Monitoring System for Ecommerce Scalability

dataforest.ai

eCommerce

Retail

Consumer products & services

Operational Inefficiencies in Price & Inventory Management

Manual monitoring of 100,000+ products across 1,500+ stores leads to high labor costs (1,000+ hours/month), frequent errors, and delayed market responsiveness. Lack of real-time competitive pricing data and stock visibility causes missed sales opportunities and customer dissatisfaction.

About the Client

Dropshipping company specializing in home furniture with 130k+ monthly orders and 1,500+ supplier stores

Strategic Goals for Market Leadership

Automate monitoring of 60 million product pages daily with <10% infrastructure costs ($1,000/month)
Reduce manual labor by 90% through AI-driven price relevance and stock availability tracking
Implement cross-platform price comparisons (Amazon, Walmart, Lowe's) for competitive advantage
Develop predictive analytics for demand forecasting (88% accuracy target)
Create automated cashback verification system to reduce order cancellations by 69%

Core System Capabilities

Distributed web scraping architecture for 60M+ daily page checks
Dynamic pricing alerts for significant market variations
Cross-platform product matching engine
Automated stockout prediction and replenishment tracking
Customizable reporting dashboard with predictive analytics
Cashback verification workflow with error detection

Technology Stack Requirements

Python

Pandas

PostgreSQL

Elasticsearch

GCP

System Integration Needs

Amazon Product API
Walmart Marketplace API
Lowe's Commercial API
Shopify Integration
Stripe Payment Verification

Performance Specifications

99.9% system uptime with distributed architecture
Sub-500ms latency for price check queries
Horizontal scalability to handle 100M+ page checks
SOC 2 Type II compliance for data security
Automated failover for supplier website outages

Projected Business Outcomes

Anticipated $5,070,000 monthly profit increase through optimized pricing strategies, 1,000+ hours monthly labor savings, 69% reduction in cashback-related cancellations, and 0.9% stockout rate improvement. The system will enable proactive market positioning through real-time competitive intelligence and predictive analytics.